Jam Tail Estimation Using Vehicle and Road Agents

Abstract

Today, an increasing number of vehicles use IoT devices to communicate with a control center to obtain such traffic information as road congestion conditions and the current shortest route. We analyze the enormous amount of data obtained from these vehicles and detect jam tails even if the percentage of vehicles with IoT devices is small. For effective performance and improved accuracy when analyzing an enormous amount of data for a wide road area, we use a multi-agent system to collect and analyze the IoT data, which is stored in memory with a hierarchical structure organized by vehicle agents and road agents. This structure enables time series data to be analyzed from the viewpoint of each vehicle and to be aggregated for jam analysis from the viewpoint of each road. Furthermore, we use a large-scale traffic simulator to evaluate the behavior of this IoT agent system.